infrastructure_allocation

The charging infrastructure allocation is based on [TracBEV[( https://github.com/rl-institut/tracbev). TracBEV is a tool for the regional allocation of charging infrastructure. In practice this allows users to use results generated via [SimBEV](https://github.com/rl-institut/simbev) and place the corresponding charging points on a map. These are split into the four use cases hpc, public, home and work.

get_data() → dict[GeoDataFrame][source]

Load all data necessary for TracBEV. Data loaded:

  • ‘hpc_positions’ - Potential hpc positions

  • ‘landuse’ - Potential work related positions

  • ‘poi_cluster’ - Potential public related positions

  • ‘public_positions’ - Potential public related positions

  • ‘housing_data’ - Potential home related positions loaded from DB

  • ‘boundaries’ - MV grid boundaries

  • miscellaneous found in datasets.yml in section charging_infrastructure

Returns # …

run_tracbev()[source]

Wrapper function to run charging infrastructure allocation

run_tracbev_potential(data_dict: dict) → None[source]

Main function to run TracBEV in potential (determination of all potential charging points).

Parameters:

data_dict (dict) – Data dict containing all TracBEV run information

run_use_cases(data_dict: dict) → None[source]

Run all use cases

Parameters:

data_dict (dict) – Data dict containing all TracBEV run information

write_to_db(gdf: GeoDataFrame, mv_grid_id: int | float, use_case: str) → None[source]

Write results to charging infrastructure DB table

Parameters:

  • gdf (geopandas.GeoDataFrame) – GeoDataFrame to save

  • mv_grid_id (int or float) – MV grid ID corresponding to the data

  • use_case (str) – Calculated use case